Publikation
Unified Multi-Modal Data Aggregation for Complementary Sensor Networks Applied for Localization
Maximilian Berndt; Dennis Krummacker; Christoph Fischer; Hans Dieter Schotten
In: Proceedings of the IEEE Vehicular Technology Conference. IEEE Vehicular Technology Conference (VTC-2022), located at 95th IEEE Vehicular Technology Conference, June 19-22, Helsinki, Finland, IEEE, 6/2022.
Zusammenfassung
Technological trends in different domains have enabled operators to integrate large numbers of sensors within their wireless communication networks.
These sensors can provide data for many different fields of applications, e.g. process monitoring, eHealth or position feedback for closed loop control of autonomous vehicles.
However, such systems often face the challenge to aggregate and process information from many distinct sources in a homogeneous and coherent manner.
We propose a software architecture design that is based on any context management and message handling system.
The general objective is to design a common interface for different information sources.
We assume that by processing this data in conjunction it can be possible to obtain enhanced quality of information.
The presented abstract architecture can enable the user to flexibly integrate different Information Anchors - active sensors or passive tags - within a comprehensive multi-modal, multi-domain data aggregation platform.
By applying a system as proposed, it is possible to generate a pool of homogeneous data sets that can be used as a sound foundation for further analysis.
We demonstrate the feasibility of the concept by presenting a possible realization of a system as described in form of an inter-operable multi-technology indoor localization system.